Principal Software Engineer, Distributed Systems...

NVIDIA Ltd.
Durham, United States of America
10 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Compensation
$ 248K

Job location

Durham, United States of America

Tech stack

API
Data Structures
Distributed Systems
Python
Software Engineering
System Programming
AI Infrastructure
Kubernetes
Information Technology
Slurm

Requirements

  • Direct experience in a software engineering role within a highly technical organization with demonstrable impact from your work. Software development experience with kubernetes APIs and frameworks not just operating a cluster.

  • Highly motivated with strong communication skills, you can work successfully with multi-functional teams, principles, and architects and coordinate effectively across organizational boundaries and geographies.

  • 15+ years in similar role and experience on large-scale production systems. Experience with common software engineering principles, tools and techniques.

  • You possess a BS in Computer Science, Engineering, Physics, Mathematics or a comparable Degree or equivalent experience.

  • Technical knowledge, including a systems programming language (Go, Python) and a solid understanding of data structures and algorithms.

Ways to stand out from the crowd:

  • Technical competency in managing and automating large-scale distributed systems independent of cloud providers. Advanced hands-on experience and deep understanding of cluster management systems (Kubernetes, Slurm, Bright Cluster Manager)

  • Proven operational excellence in maintaining reliable and performant AI infrastructure.

Benefits & conditions

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 248,000 USD - 396,750 USD.

About the company

NVIDIA is hiring experienced software engineers with kubernetes experience to help scale up its AI Infrastructure. We expect you to have significant software engineering experience with kubernetes including cluster operations, operator development, node health monitoring and working with GPU resource scheduling. We welcome out-of-the-box thinkers who can provide new ideas with strong execution bias. Expect to be constantly challenged, improving, and evolving for the better. You will help advance NVIDIA's capacity to build and deploy leading infrastructure solutions for a broad range of AI-based applications. If you're creative, passionate about kubernetes and GPUs, and love having fun, please apply today! For two decades, we have pioneered visual computing, the art and science of computer graphics. With the invention of the GPU - the engine of modern visual computing - the field has expanded to encompass video games, movie production, product design, medical diagnosis and scientific research. Today, we stand at the beginning of the next era, the AI computing era, ignited by a new computing model, GPU deep learning. What you will be doing: + You will be part of an DGX Cloud team responsible for production systems that enable large scalable GPU clusters to be used for a variety of AI workloads. This includes working on custom software related to scheduling GPU resources on kubernetes. + Implementing monitoring and health management capabilities that enable industry leading reliability, availability, and scalability of GPU assets. You will be harnessing multiple data streams, ranging from GPU hardware diagnostics to cluster and network telemetry. + Working with teams across NVIDIA to ensure production AI clusters run reliability and consistently with maximum performance. Evaluating system failures and improving services based on a well-defined incident management process., NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you are creative and autonomous, we want to hear from you!

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